Addressing wavelength-correlated systematics in exoplanet transmission spectroscopy: a 2D Gaussian Process approach

TL;DR

This paper introduces a 2D Gaussian Process method to model both time- and wavelength-correlated systematics in ground-based exoplanet transmission spectroscopy, improving atmospheric characterization accuracy.

Contribution

It applies a novel 2D GP framework to account for wavelength-correlated systematics, enhancing the robustness of exoplanet atmospheric retrievals from ground-based data.

Findings

Successful application to TOI-4153b observations

Improved modeling of wavelength-correlated systematics

Enhanced accuracy in atmospheric parameter estimation

Abstract

Ground-based transmission spectroscopy is often dominated by systematics, which obstructs our ability to leverage the advantages of larger aperture sizes compared to space-based observations. These systematics could be time-correlated, uniform across all spectroscopic light curves, or wavelength-correlated, which could significantly affect the characterization of exoplanet atmospheres. Gaussian Processes were introduced in transmission spectroscopy by Gibson et al. (2012) to model correlated systematics in a non-parametric way. The technique uses auxiliary information about the observation and independently fits each spectroscopic light curve to provide robust atmospheric retrievals. However, this method assumes that the uncertainties in the transmission spectrum are uncorrelated in wavelength, which can cause discrepancies and degrade the precision of atmospheric retrievals. To address this limitation, we explore a 2D GP framework formulated by Fortune et al. (2024) to simultaneously model time- and wavelength-correlated systematics. We present its application to ground-based observations of TOI-4153b obtained using the 2-m Himalayan Chandra Telescope (HCT). As we move towards detecting smaller and cooler planets, developing new methods to address complex systematics becomes increasingly essential.